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Executive Summary:

Given that AI technologies are evolving at a fast pace in 2024, an AI-oriented phishing attack on a large Indian financial institution illustrated the threats. The documentation of the attack specifics involves the identification of attack techniques, ramifications to the institution, intervention conducted, and resultant effects. The case study also turns to the challenges connected with the development of better protection and sensibilisation of automatized threats. 

Introduction

Due to the advancement in AI technology, its uses in cybercrimes across the world have emerged significant in financial institutions. In this report a serious incident that happened in early 2024 is analysed, according to which a leading Indian bank was hit by a highly complex, highly intelligent AI-supported phishing operation. Attack made use of AI’s innate characteristic of data analysis and data persuasion which led into a severe compromise of the bank’s internal structures.

Background

The chosen financial institution, one of the largest banks in India, had a good background regarding the extremity of its cybersecurity policies. However, these global cyberattacks opened up new threats that AI-based methods posed that earlier forms of security could not entirely counter efficiently. The attackers concentrated on the top managers of the bank because it is evident that controlling such persons gives the option of entering the inner systems as well as financial information. 

Attack Execution

The attackers utilised AI in sending the messages that were an exact look alike of internal messages sent between employees. From Facebook and Twitter content, blog entries, and lastly, LinkedIn connection history and email tenor of the bank’s executives, the AI used to create these emails was highly specific. Some of these emails possessed official formatting, specific internal language, and the CEO’s writing; this made them very realistic. 

 It also used that link in phishing emails that led the users to a pseudo internal portal in an attempt to obtain the login credentials. Due to sophistication, the targeted individuals thought the received emails were genuine, and entered their log in details easily to the bank’s network, thus allowing the attackers access. 

Impact

It caused quite an impact to the bank in every aspect. Numerous executives of the company lost their passwords to the fake emails and compromised several financial databases with information from customer accounts and transactions. The break-in permitted the criminals to cease a number of the financial’s internet services hence disrupting its functions and those of its customers for a number of days. 

 They also suffered a devastating blow to their customer trust because the breach revealed the bank’s weakness against contemporary cyber threats. Apart from managing the immediate operations which dealt with mitigating the breach, the financial institution was also toppling a long-term reputational hit. 

Technical Analysis and Findings

1. The AI techniques that are used in generation of the phishing emails are as follows: 

•  The attack used powerful NLP technology, which was most probably developed using the large-scaled transformer, such as GPT (Generative Pre-trained Transformer). Since these models are learned from large data samples they used the examples of the conversation pieces from social networks, emails and PC language to create quite credible emails. 

 Key Technical Features: 

•  Contextual Understanding: The AI was able to take into account the nature of prior interactions and thus write follow up emails that were perfectly in line with prior discourse. 
•  Style Mimicry: The AI replicated the writing of the CEO given the emails of the CEO and then extrapolated from the data given such elements as the tone, the language, and the format of the signature line. 
•  Adaptive Learning: The AI actively adapted from the mistakes, and feedback to tweak the generated emails for other tries and this made it difficult to detect. 

2. Sophisticated Spear-Phishing Techniques

Unlike ordinary phishing scams, this attack was phishing using spear-phishing where the attackers would directly target specific people using emails. The AI used social engineering techniques that significantly increased the chances of certain individuals replying to certain emails based on algorithms which machine learning furnished. 

 Key Technical Features: 

•  Targeted Data Harvesting: Cyborgs found out the employees of the organisation and targeted messages via the public profiles and messengers were scraped. 
•  Behavioural Analysis: The latest behaviour pattern concerning the users of the social networking sites and other online platforms were used by the AI to forecast the courses of action expected to be taken by the end users such as clicking on the links or opening of the attachments. 
•  Real-Time Adjustments: These are times when it was determined that the response to the phishing email was necessary and the use of AI adjusted the consequent emails’ timing and content. 

3. Advanced Evasion Techniques

The attackers were able to pull off this attack by leveraging AI in their evasion from the normal filters placed in emails. These techniques therefore entailed a modification of the contents of the emails in a manner that would not be easily detected by the spam filters while at the same time preserving the content of the message. 

Key Technical Features: 

•  Dynamic Content Alteration: The AI merely changed the different aspects of the email message slightly to develop several versions of the phishing email that would compromise different algorithms. 
•  Polymorphic Attacks: In this case, polymorphic code was used in the phishing attack which implies that the actual payloads of the links changed frequently, which means that it was difficult for the AV tools to block them as they were perceived as threats. 
•  Phantom Domains: Another tactic employed was that of using AI in generating and disseminating phantom domains, that are actual web sites that appear to be legitimate but are in fact short lived specially created for this phishing attack, adding to the difficulty of detection. 

4. Exploitation of Human Vulnerabilities

This kind of attack’s success was not only in AI but also in the vulnerability of people, trust in familiar language and the tendency to obey authorities. 

Key Technical Features: 

•  Social Engineering: As for the second factor, AI determined specific psychological principles that should be used in order to maximise the chance of the targeted recipients opening the phishing emails, namely the principles of urgency and familiarity. 
•  Multi-Layered Deception: The AI was successfully able to have a two tiered approach of the emails being sent as once the targeted individuals opened the first mail, later the second one by pretext of being a follow up by a genuine company/personality. 

Response

On sighting the breach, the bank’s cybersecurity personnel spring into action to try and limit the fallout. They reported the matter to the Indian Computer Emergency Response Team (CERT-In) to find who originated the attack and how to block any other intrusion. The bank also immediately started taking measures to strengthen its security a bit further, for instance, in filtering emails, and increasing the authentication procedures. 

 Knowing the risks, the bank realised that actions should be taken in order to enhance the cybersecurity level and implement a new wide-scale cybersecurity awareness program. This programme consisted of increasing the awareness of employees about possible AI-phishing in the organisation’s info space and the necessity of checking the sender’s identity beforehand.

Outcome

Despite the fact and evidence that this bank was able to regain its functionality after the attack without critical impacts with regards to its operations, the following issues were raised. Some of the losses that the financial institution reported include losses in form of compensation of the affected customers and costs of implementing measures to enhance the financial institution’s cybersecurity. However, the principle of the incident was significantly critical of the bank as customers and shareholders began to doubt the organisation’s capacity to safeguard information in the modern digital era of advanced artificial intelligence cyber threats. 

 This case depicts the importance for the financial firms to align their security plan in a way that fights the new security threats. The attack is also a message to other organisations in that they are not immune from such analysis attacks with AI and should take proper measures against such threats.

Conclusion

The recent AI-phishing attack on an Indian bank in 2024 is one of the indicators of potential modern attackers’ capabilities. Since the AI technology is still progressing, so are the advances of the cyberattacks. Financial institutions and several other organisations can only go as far as adopting adequate AI-aware cybersecurity solutions for their systems and data. 

 Moreover, this case raises awareness of how important it is to train the employees to be properly prepared to avoid the successful cyberattacks. The organisation’s cybersecurity awareness and secure employee behaviours, as well as practices that enable them to understand and report any likely artificial intelligence offences, helps the organisation to minimise risks from any AI attack.

Recommendations

1. Enhanced AI-Based Defences: Financial institutions should employ AI-driven detection and response products that are capable of mitigating AI-operation-based cyber threats in real-time. 
2.  Employee Training Programs: CYBER SECURITY: All employees should undergo frequent cybersecurity awareness training; here they should be trained on how to identify AI-populated phishing. 
3.  Stricter Authentication Protocols: For more specific accounts, ID and other security procedures should be tight in order to get into sensitive ones. 
4.  Collaboration with CERT-In: Continued engagement and coordination with authorities such as the Indian Computer Emergency Response Team (CERT-In) and other equivalents to constantly monitor new threats and valid recommendations. 
5.  Public Communication Strategies: It is also important to establish effective communication plans to address the customers of the organisations and ensure that they remain trusted even when an organisation is facing a cyber threat. 

Through implementing these, financial institutions have an opportunity for being ready with new threats that come with AI and cyber terrorism on essential financial assets in today’s complex IT environments.

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Introduction

On May 21st, 2025, the Department of Telecommunications (DoT) launched the Financial Risk Indicator (FRI) feature, marking an important step towards safeguarding mobile phone users from the risks of financial fraud. This was developed as a part of the Digital Intelligence Platform (DIP), which facilitates coordination between stakeholders to curb the misuse of telecom services for conducting cyber crimes.

What is the Financial Risk Indicator (FRI)?

The FRI is a risk-based metric feature that categorises phone numbers into risk, medium risk, and high risk based on their association with financial fraud in the past. The data pool enabling this intelligence sharing includes the Digital Intelligence Unit (DIU) of the DoT, which engages and sends a list of Mobile Numbers that were disconnected (Mobile Number Revocation List - MNRL) to the following stakeholders, creating a network of checks and balances. They are:

1. Intelligence from Non-Banking Finance Companies, and UPI (Unified Payment Interface) gateways.
2. The Chakshu facility- a feature on the Sanchar Saathi portal that enables users to report suspected fraudulent communication (Calls, SMS, WhatsApp messages), which has also been roped in.
3. Complaints from the National Cybercrime Reporting Portal (NCRP) through the I4C (Indian Cyber Coordination Center).

Some other initiatives taken up concerning securing against digital financial fraud are the Citizen Financial Cyber Fraud Reporting and Management System, the International Incoming Spoofed Calls Prevention System, among others.

A United Stance

The ease of payment and increasing digitisation might have enabled the increasing usage of UPI platforms. However, post-adoption, the responsibility of securing the digital payments infrastructure becomes essential. As per a report by CNBC TV18, UPI fraud cases surged by 85% in FY24. The number of incidents have increased from 7.25 lakh in FY23 to 13.42 lakh in FY24. These cases involved a total value of ₹1,087 crore, compared to ₹573 crore in the previous year, and the number continues to increase. 

Nevertheless, UPI platforms are taking their own initiative to combat such crimes. PhonePe, one of the most used digital payment interface as of January 2025 (Statista) has already incorporated the FRI into its PhonePe Protect feature; this blocks transactions with high-risk numbers and issues a warning prior to engaging with numbers that are categorised to be of medium risk. 

CyberPeace Insights

The launch of a feature addressing the growing threat of financial fraud is crucial for creating a network of stakeholders to coordinate with law enforcement to better track and prevent crimes. Publicity of these measures will raise public awareness and keep end-users informed. A secure infrastructure for digital payments is necessary in this age, with a robust base mechanism that can adapt to both current and future threats.

References

• https://www.thehawk.in/news/economy-and-business/centre-launches-financial-fraud-risk-indicator-to-safeguard-mobile-users
• https://telanganatoday.com/government-launches-financial-fraud-risk-indicator-to-safeguard-mobile-users
• https://www.pib.gov.in/PressReleasePage.aspx?PRID=2130249#:~:text=What%20is%20the%20%E2%80%9CFinancial%20Fraud,High%20risk%20of%20financial%20fraud
• https://www.business-standard.com/industry/news/dot-launches-financial-fraud-risk-indicator-to-aid-cybercrime-detection-125052101912_1.html 
• https://www.cnbctv18.com/business/finance/upi-fraud-cases-rise-85-pc-in-fy24-increase-parliament-reply-data-19514295.htm
• https://www.statista.com/statistics/1034443/india-upi-usage-by-platform/#:~:text=In%20January%202025%2C%20PhonePe%20held%20the%20highest,key%20drivers%20of%20UPI%20adoption%20in%20India
• https://telecom.economictimes.indiatimes.com/amp/news/policy/centre-notifies-draft-rules-for-delicensing-lower-6-ghz-band/121260887?nt

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Executive Summary:

Internship scams have infiltrated the academic landscape, scamming students of many prestigious colleges. The students often prefer to carry out internships to gain knowledge and work experience. These scams use the name of popular multinational companies to exploit the students. This report studies the various case studies, their modus operandi, impact on the students and preventive strategies. This report emphasises the importance of awareness and proactive measures to protect students from falling victim to such frauds.

1. Introduction

Internships are the opportunity to overcome the gap between the practical knowledge acquired at the university and practical experience, to get practical skills and contacts in the field of activity, as well as improve employment prospects. Instead, because of high paying internships and interesting positions students have become targets of work scams. As we have seen with the advancement in digital technology, scammers take advantage of the disguise of the internet, making very neat, smart, and convincing scams. 

 Internship scams are very prevalent and they include fake job listings and phishing schemes as well as payment frauds which make students lose lots of money and also emotionally expose them. In this specific case, this paper examines how these scams work, the warning signs, and ways of protecting students from falling victim to them.

2. Detailed Modus Operandi of Internship Scams

Internship scams often employ  a variety of tactics to attract and deceive unsuspecting students. Below is a detailed breakdown of the common methods used by scammers:

1. Fake Job Listings and Offers:some text
   • Scammers post attractive internship offers on popular job portals, social media platforms, and even send personalised messages via LinkedIn. These listings often mimic the branding and style of reputable companies, including well-designed logos, professional email addresses, and official-looking websites.
   • Example: A fake internship offer from a reputed software firm circulates on a job portal, with a professional landing page. Students who apply are quickly “hired” without any interviews, and are asked to pay a security deposit to confirm their acceptance.
2. Upfront Payment Requests:some text
   • Scammers ask for payment such as registration fees, training materials, background checks, or security deposits. These payments comes under non-refundable payment  and it act as the primary revenue stream for the fraudsters.
   • Example: A group of students receive internship offers requiring a payment of INR 10,000 for "training materials" and "online assessments." After making the payment, the students never hear back from the company, and all attempts to contact them were futile.
3. Phishing and Identity Theft:some text
   • Beyond financial fraud, some scams aim to steal personal information. Fake internship applications often require detailed personal data, including identity proofs, bank account details. This data will be used as identity theft or sold on the dark web.
   • Example: A student applies for an internship that asks for copies of identification documents and bank details. This information sharing led to unauthorised transactions in their bank account. 
4. Work-from-Home Frauds:some text
   • With the rise of remote work, scammers also offer work-from-home internships that require students to purchase software or pay for specialised training. After payment, students are often given irrelevant tasks or no tasks at all, leaving them with no real work experience.
   • Example: An internship advertised as a "remote data analysis role" required students to buy a proprietary software licence. After paying, students realised the software was freely available online, and the internship tasks were non-existent.
5. Impersonation of Reputed Companies:some text
   • Scammers use the name of well-known companies, they modify the email addresses or create fake websites that look original. They use these platforms to send offer letters, making it difficult for students to identify the scam.
   • Example: A scammer creates a fake website mirroring a major consulting firm's internship page. The only difference is a minor change in the URL. Dozens of students are duped into paying registration fees.

3. Case Studies of Real-Life Incidents

1. Case Study 1: The Certification Course and Internshipsome text
   • A group of students received personalised emails from an official domain of a reputed tech industry providing an internship offer. Students were asked to pay Rs 10,000 to undergo a certification course to carry the internship. After paying the amount, the students did not receive any instructions, and the company was found to be nonexistent. The scammer had spoofed the company’s email domain, making it difficult to trace the source.
2. Case Study 2: The Social Media Trapsome text
   • A student from a university encountered an internship post on Instagram, advertising roles at a popular fashion brand. The application process involved a "screening fee" of INR 5,000. Despite appearing legitimate, the internship was fake, and the brand had no knowledge of the post. The student's personal data was also compromised, leading to unauthorised social media activity.
3. Case Study 3: Internship Providing Social Platformssome text
   • A popular internship providing platform, faced an incident where a scammer posted fraudulent internship offers under the guise of a major multinational. The scam involved asking students to purchase expensive software to start their work. The platform had to issue warnings and remove the listings after several complaints.

4. The Impact on Students

The consequences of internship scams extend beyond immediate financial loss, affecting students on multiple levels:

1. Financial Impact:some text
   • Students lose their money, ranging from minor fees to significant payments.
2. Emotional and Psychological Distress:some text
   • These kinds of scams can lead to anxiety, depression and loss of confidence in availing the opportunities in future. 
3. Exposure to Further Scams:some text
   • Scammers often share details of their victims with other fraudsters, making students susceptible to repeated scams, including phishing attacks, financial frauds, and unsolicited offers.

5. Preventive Measures

1. Verification of Internships:some text
   • Always verify the authenticity of the internship by researching the company on official platforms such as LinkedIn, the company’s official website, and through trusted contacts or college placement cells.
2. Avoid Upfront Payments:some text
   • Employers do not ask for money in exchange for job or internship offers. If they demand for any kind of payment, then the employer is not original. Always question the necessity of such payments and consult trusted advisors before proceeding.
3. Use Trusted Job Portals:some text
   • Apply for internships through recognized platforms like LinkedIn, Internshala, or your college’s placement cell, which have verification processes to filter out fraudulent postings.
4. Reporting Scams:some text
   • Report suspicious offers to your college authorities, placement cells, and local cybercrime departments. Additionally, use platforms like Internshala’s “Report This Job” feature to flag fraudulent listings.
5. Stay Educated and Updated:some text
   • It is important to educate students by providing workshops, webinars, and awareness sessions on cybersecurity to stay informed and report about the latest scams. 

6. Conclusion

Internship scams are a severe threat to the student society since they manipulate the student’s desire for an internship. The best ways to prevent such cons are by being cautious and receptive to whatever is being offered. Internship seekers, colleges and the placement cells have to work hand in hand to ensure that there is no fear among  people seeking internships.

References

1. Smith, J. (2024). Internship Scams on the Rise: How to Spot and Avoid Them. Retrieved from example1.com.
2. Brown, A. (2023). Student Internship Scams in India: A Growing Concern. Retrieved from example2.com.
3. Johnson, L. (2024). How to Protect Yourself from Fake Internship Offers. Retrieved from example3.com.
4. Gupta, R. (2024). Social Media and the Rise of Job Scams. Retrieved from example4.com.

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